Changes in First-Year Students’ Use of Research Resources: Impacts of an Interdisciplinary Seminar Program on Research and Literacy Learning Outcomes
Bibliographic record
Abstract
The Internet, which has made information ubiquitous and seemingly infinite, has transformed education. Universities are challenged to educate students to navigate and evaluate critically the undifferentiated information of the Internet so that students gain the ability to transform it into knowledge. To better understand the effects of taking a First-Year Seminar we examined the types of research resources students consulted before and after taking an interdisciplinary graded for-credit First-Year Seminar at a midsize comprehensive public university in Canada. We analyzed 2,576 anonymous questionnaires collected across 102 first-year seminars. After completing a first-year seminar, students consulted more reliable and scholarly resources, irrespective of the semester of enrollment. Generally, there were some improvements noted between first and second semester students. However, comparisons between students who had just completed a seminar in semester one with students who were about to begin a seminar in semester two, reveal that the improved results are not solely attributable to the normal transition and maturation process experienced by students in their first semester of university. L’Internet, qui a rendu l’information omniprésente et apparemment inépuisable, a transformé l’éducation. Les universités sont mises au défi d’enseigner aux étudiants comment naviguer et évaluer de façon critique les informations non différenciées trouvées sur Internet afin que les étudiants puissent apprendre à transformer ces informations en connaissances. Pour mieux comprendre les effets sur les étudiants qui suivent un séminaire de première année, nous avons examiné les divers types de ressources de recherche que les étudiants ont consultées avant et après avoir suivi un séminaire interdisciplinaire noté et menant à l’obtention d’un crédit, dans une université canadienne publique de taille moyenne. Nous avons analysé 2 576 questionnaires anonymes obtenus de 102 séminaires de première année. Après avoir suivi un séminaire de première année, les étudiants ont consulté des ressources plus fiables et plus savantes, indifféremment du semestre dans lequel ils se trouvaient à ce moment-là. En général, on a noté quelques améliorations entre les étudiants de premier semestre et ceux de deuxième semestre. Toutefois, les comparaisons entre les étudiants qui venaient de terminer un séminaire au cours de leur premier semestre et les étudiants qui étaient sur le point de commencer un séminaire au cours de leur deuxième semestre ont révélé que les meilleurs résultats ne sont pas exclusivement attribuables à la transition normale et au processus de maturation dont les étudiants font l’expérience au cours de leur premier semestre.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".